Correlation Between Bank Rakyat and Argo Pantes
Can any of the company-specific risk be diversified away by investing in both Bank Rakyat and Argo Pantes at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Bank Rakyat and Argo Pantes into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Rakyat Indonesia and Argo Pantes Tbk, you can compare the effects of market volatilities on Bank Rakyat and Argo Pantes and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Bank Rakyat with a short position of Argo Pantes. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Rakyat and Argo Pantes.
Diversification Opportunities for Bank Rakyat and Argo Pantes
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and Argo is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Bank Rakyat Indonesia and Argo Pantes Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Argo Pantes Tbk and Bank Rakyat is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Bank Rakyat Indonesia are associated (or correlated) with Argo Pantes. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Argo Pantes Tbk has no effect on the direction of Bank Rakyat i.e., Bank Rakyat and Argo Pantes go up and down completely randomly.
Pair Corralation between Bank Rakyat and Argo Pantes
Assuming the 90 days trading horizon Bank Rakyat Indonesia is expected to under-perform the Argo Pantes. But the stock apears to be less risky and, when comparing its historical volatility, Bank Rakyat Indonesia is 1.6 times less risky than Argo Pantes. The stock trades about -0.36 of its potential returns per unit of risk. The Argo Pantes Tbk is currently generating about -0.19 of returns per unit of risk over similar time horizon. If you would invest 109,000 in Argo Pantes Tbk on September 1, 2024 and sell it today you would lose (11,500) from holding Argo Pantes Tbk or give up 10.55% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.45% |
| Values | Daily Returns |
Bank Rakyat Indonesia vs. Argo Pantes Tbk
Performance |
| Timeline |
| Bank Rakyat Indonesia |
| Argo Pantes Tbk |
Bank Rakyat and Argo Pantes Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank Rakyat and Argo Pantes
The main advantage of trading using opposite Bank Rakyat and Argo Pantes positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Rakyat position performs unexpectedly, Argo Pantes can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Argo Pantes will offset losses from the drop in Argo Pantes' long position.| Bank Rakyat vs. Bank Central Asia | Bank Rakyat vs. Bank Mandiri Persero | Bank Rakyat vs. Bank Negara Indonesia | Bank Rakyat vs. Telkom Indonesia Tbk |
| Argo Pantes vs. Japfa Comfeed Indonesia | Argo Pantes vs. Charoen Pokphand Indonesia | Argo Pantes vs. Erajaya Swasembada Tbk | Argo Pantes vs. Indofood Cbp Sukses |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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